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TreeSpider: JavaScript library for displaying organization structure

Hacker News

TreeSpider: JavaScript library for displaying organization structure

I'm introducing TreeSpider, an free & open source organization structure/tree library completely written in object oriented TypeScript and D3js, for displaying organization structure in style, it comes with different beautiful tree types and it is highly customizable and it also fits companies with flat organization structure If your company needs to visualize the employees in the organization, TreeSpider is the best for it It is completely free and open source, and it seems like it is the most advanced, free and open source, organization structure/tree library out there right now GitHub repo and contributions and/or feature requests are welcome https://github.com/paulosabayomi/treeSpider homepage and documentation https://treespider.pryxy.com Get it on npm https://www.npmjs.com/package/treespider

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, open · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, ide, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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